A molecular barcode to inform the geographical origin and transmission dynamics of Plasmodium vivax malaria

Microsatellites markers fostering the understanding of malaria parasite biology, epidemiology and population genetics

Microsatellites, or simple sequence repeats (SSRs), are short tandemly repeated DNA sequences widely dispersed throughout the genome. Their high variability, co-dominant inheritance, and ease of detection make them valuable genetic markers, frequently used to study genetic diversity, population structure, and evolutionary processes. In the context of malaria research, particularly with Plasmodium falciparum (P.falciparum), the deadliest malaria parasite in humans, microsatellites have been extensively utilized to track genetic variation, monitor drug resistance, and understand transmission patterns. This study highlights the significance of microsatellite markers in unraveling the genetic complexity of P. falciparum, providing insights into its biology and epidemiology. We discuss their application in the study of parasite population genetics, the challenges associated with their use, and their potential in guiding malaria control strategies. By focusing on P. falciparum, this work emphasizes the critical role of microsatellite markers in advancing our understanding of malaria transmission, drug resistance, and potential vaccine development.

Plasmodium vivax populations in the western Greater Mekong Subregion evaluated using a genetic barcode

An improved understanding of the Plasmodium vivax populations in the Great Mekong Subregion (GMS) is needed to monitor the progress of malaria elimination. This study aimed to use a P. vivax single nucleotide polymorphism (SNP) barcode to evaluate the population dynamics and explore the gene flow among P. vivax parasite populations in the western GMS (China, Myanmar and Thailand). A total of 315 P. vivax patient samples collected in 2011 and 2018 from four regions of the western GMS were genotyped for 42 SNPs using the high-throughput MassARRAY SNP genotyping technology. Population genetic analysis was conducted to estimate the genetic diversity, effective population size, and population structure among the P. vivax populations. Overall, 291 samples were successfully genotyped at 39 SNPs. A significant difference was observed in the proportion of polyclonal infections among the five P. vivax populations (P = 0.0012, Pearson Chi-square test, χ2 = 18.1), with western Myanmar having the highest proportion (96.2%, 50/52) in 2018. Likewise, the average complexity of infection was also highest in western Myanmar (1.31) and lowest in northeast Myanmar (1.01) in 2018. The older samples from western China in 2011 had the highest pairwise nucleotide diversity (π, 0.388 ± 0.046), expected heterozygosity (He, 0.363 ± 0.02), and the largest effective population size. In comparison, in the neighboring northeast Myanmar, the more recent samples in 2018 showed the lowest values (π, 0.224 ± 0.036; He, 0.220 ± 0.026). Furthermore, the 2018 northeast Myanmar parasites showed high and moderate genetic differentiation from other populations with FST values of 0.162-0.252, whereas genetic differentiation among other populations was relatively low (FST ≤ 0.059). Principal component analysis, phylogeny, and STRUCTURE analysis showed that the P. vivax population in northeast Myanmar in 2018 substantially diverged from other populations. Although the 42 SNP barcode is a valuable tool for tracking parasite origins of worldwide parasite populations, a more extended barcode with additional SNPs is needed to distinguish the more related parasite populations in the western GMS.

Molecular markers for malaria genetic epidemiology: progress and pitfalls

Over recent years, progress in molecular markers for genotyping malaria parasites has enabled informative studies of epidemiology and transmission dynamics. Results have highlighted the value of these tools for surveillance to support malaria control and elimination strategies. There are many different types and panels of markers available for malaria parasite genotyping, and for end users, the nuances of these markers with respect to 'use case', resolution, and accuracy, are not well defined. This review clarifies issues surrounding different molecular markers and their application to malaria control and elimination. We describe available marker panels, use cases, implications for different transmission settings, limitations, access, cost, and data accuracy. The information provided can be used as a guide for molecular epidemiology and surveillance of malaria.

Rapid profiling of Plasmodium parasites from genome sequences to assist malaria control

BACKGROUND

Malaria continues to be a major threat to global public health. Whole genome sequencing (WGS) of the underlying Plasmodium parasites has provided insights into the genomic epidemiology of malaria. Genome sequencing is rapidly gaining traction as a diagnostic and surveillance tool for clinical settings, where the profiling of co-infections, identification of imported malaria parasites, and detection of drug resistance are crucial for infection control and disease elimination. To support this informatically, we have developed the Malaria-Profiler tool, which rapidly (within minutes) predicts Plasmodium species, geographical source, and resistance to antimalarial drugs directly from WGS data.

RESULTS

The online and command line versions of Malaria-Profiler detect ~ 250 markers from genome sequences covering Plasmodium speciation, likely geographical source, and resistance to chloroquine, sulfadoxine-pyrimethamine (SP), and other anti-malarial drugs for P. falciparum, but also providing mutations for orthologous resistance genes in other species. The predictive performance of the mutation library was assessed using 9321 clinical isolates with WGS and geographical data, with most being single-species infections (P. falciparum 7152/7462, P. vivax 1502/1661, P. knowlesi 143/151, P. malariae 18/18, P. ovale ssp. 5/5), but co-infections were identified (456/9321; 4.8%). The accuracy of the predicted geographical profiles was high to both continental (96.1%) and regional levels (94.6%). For P. falciparum, markers were identified for resistance to chloroquine (49.2%; regional range: 24.5% to 100%), sulfadoxine (83.3%; 35.4- 90.5%), pyrimethamine (85.4%; 80.0-100%) and combined SP (77.4%). Markers associated with the partial resistance of artemisinin were found in WGS from isolates sourced from Southeast Asia (30.6%).

CONCLUSIONS

Malaria-Profiler is a user-friendly tool that can rapidly and accurately predict the geographical regional source and anti-malarial drug resistance profiles across large numbers of samples with WGS data. The software is flexible with modifiable bioinformatic pipelines. For example, it is possible to select the sequencing platform, display specific variants, and customise the format of outputs. With the increasing application of next-generation sequencing platforms on Plasmodium DNA, Malaria-Profiler has the potential to be integrated into point-of-care and surveillance settings, thereby assisting malaria control. Malaria-Profiler is available online (bioinformatics.lshtm.ac.uk/malaria-profiler) and as standalone software ( https://github.com/jodyphelan/malaria-profiler ).

Sampling for malaria molecular surveillance

Strategic use of Plasmodium falciparum genetic variation has great potential to inform public health actions for malaria control and elimination. Malaria molecular surveillance (MMS) begins with a strategy to identify and collect parasite samples, guided by public-health priorities. In this review we discuss sampling design practices for MMS and point out epidemiological, biological, and statistical factors that need to be considered. We present examples for different use cases, including detecting emergence and spread of rare variants, establishing transmission sources and inferring changes in malaria transmission intensity. This review will potentially guide the collection of samples and data, serve as a starting point for further methodological innovation, and enhance utilization of MMS to support malaria elimination.

minSNPs: an R package for the derivation of resolution-optimised SNP sets from microbial genomic data

Here, we present the R package, minSNPs. This is a re-development of a previously described Java application named Minimum SNPs. MinSNPs assembles resolution-optimised sets of single nucleotide polymorphisms (SNPs) from sequence alignments such as genome-wide orthologous SNP matrices. MinSNPs can derive sets of SNPs optimised for discriminating any user-defined combination of sequences from all others. Alternatively, SNP sets may be optimised to determine all sequences from all other sequences, i.e., to maximise diversity. MinSNPs encompasses functions that facilitate rapid and flexible SNP mining, and clear and comprehensive presentation of the results. The minSNPs' running time scales in a linear fashion with input data volume and the numbers of SNPs and SNPs sets specified in the output. MinSNPs was tested using a previously reported orthologous SNP matrix of Staphylococcus aureus and an orthologous SNP matrix of 3,279 genomes with 164,335 SNPs assembled from four S. aureus short read genomic data sets. MinSNPs was shown to be effective for deriving discriminatory SNP sets for potential surveillance targets and in identifying SNP sets optimised to discriminate isolates from different clonal complexes. MinSNPs was also tested with a large Plasmodium vivax orthologous SNP matrix. A set of five SNPs was derived that reliably indicated the country of origin within three south-east Asian countries. In summary, we report the capacity to assemble comprehensive SNP matrices that effectively capture microbial genomic diversity, and to rapidly and flexibly mine these entities for optimised marker sets.

Population dynamics and drug resistance mutations in Plasmodium falciparum on the Bijagós Archipelago, Guinea-Bissau

Following integrated malaria control interventions, malaria burden on the Bijagós Archipelago has significantly decreased. Understanding the genomic diversity of circulating Plasmodium falciparum malaria parasites can assist infection control, through identifying drug resistance mutations and characterising the complexity of population structure. This study presents the first whole genome sequence data for P. falciparum isolates from the Bijagós Archipelago. Amplified DNA from P. falciparum isolates sourced from dried blood spot samples of 15 asymptomatic malaria cases were sequenced. Using 1.3 million SNPs characterised across 795 African P. falciparum isolates, population structure analyses revealed that isolates from the archipelago cluster with samples from mainland West Africa and appear closely related to mainland populations; without forming a separate phylogenetic cluster. This study characterises SNPs associated with antimalarial drug resistance on the archipelago. We observed fixation of the PfDHFR mutations N51I and S108N, associated with resistance to sulphadoxine-pyrimethamine, and the continued presence of PfCRT K76T, associated with chloroquine resistance. These data have relevance for infection control and drug resistance surveillance; particularly considering expected increases in antimalarial drug use following updated WHO recommendations, and the recent implementation of seasonal malaria chemoprevention and mass drug administration in the region.

A molecular barcode and web-based data analysis tool to identify imported Plasmodium vivax malaria

Traditionally, patient travel history has been used to distinguish imported from autochthonous malaria cases, but the dormant liver stages of Plasmodium vivax confound this approach. Molecular tools offer an alternative method to identify, and map imported cases. Using machine learning approaches incorporating hierarchical fixation index and decision tree analyses applied to 799 P. vivax genomes from 21 countries, we identified 33-SNP, 50-SNP and 55-SNP barcodes (GEO33, GEO50 and GEO55), with high capacity to predict the infection's country of origin. The Matthews correlation coefficient (MCC) for an existing, commonly applied 38-SNP barcode (BR38) exceeded 0.80 in 62% countries. The GEO panels outperformed BR38, with median MCCs > 0.80 in 90% countries at GEO33, and 95% at GEO50 and GEO55. An online, open-access, likelihood-based classifier framework was established to support data analysis (vivaxGEN-geo). The SNP selection and classifier methods can be readily amended for other use cases to support malaria control programs.

Geographical classification of malaria parasites through applying machine learning to whole genome sequence data

Malaria, caused by Plasmodium parasites, is a major global health challenge. Whole genome sequencing (WGS) of Plasmodium falciparum and Plasmodium vivax genomes is providing insights into parasite genetic diversity, transmission patterns, and can inform decision making for clinical and surveillance purposes. Advances in sequencing technologies are helping to generate timely and big genomic datasets, with the prospect of applying Artificial Intelligence analytical techniques (e.g., machine learning) to support programmatic malaria control and elimination. Here, we assess the potential of applying deep learning convolutional neural network approaches to predict the geographic origin of infections (continents, countries, GPS locations) using WGS data of P. falciparum (n = 5957; 27 countries) and P. vivax (n = 659; 13 countries) isolates. Using identified high-quality genome-wide single nucleotide polymorphisms (SNPs) (P. falciparum: 750 k, P. vivax: 588 k), an analysis of population structure and ancestry revealed clustering at the country-level. When predicting locations for both species, classification (compared to regression) methods had the lowest distance errors, and > 90% accuracy at a country level. Our work demonstrates the utility of machine learning approaches for geo-classification of malaria parasites. With timelier WGS data generation across more malaria-affected regions, the performance of machine learning approaches for geo-classification will improve, thereby supporting disease control activities.

Population genomics in neglected malaria parasites

Malaria elimination includes neglected human malaria parasites Plasmodium vivax, Plasmodium ovale spp., and Plasmodium malariae. Biological features such as association with low-density infection and the formation of hypnozoites responsible for relapse make their elimination challenging. Studies on these parasites rely primarily on clinical samples due to the lack of long-term culture techniques. With improved methods to enrich parasite DNA from clinical samples, whole-genome sequencing of the neglected malaria parasites has gained increasing popularity. Population genomics of more than 2200 P. vivax global isolates has improved our knowledge of parasite biology and host-parasite interactions, identified vaccine targets and potential drug resistance markers, and provided a new way to track parasite migration and introduction and monitor the evolutionary response of local populations to elimination efforts. Here, we review advances in population genomics for neglected malaria parasites, discuss how the rich genomic information is being used to understand parasite biology and epidemiology, and explore opportunities for the applications of malaria genomic data in malaria elimination practice.

Novel highly-multiplexed AmpliSeq targeted assay for Plasmodium vivax genetic surveillance use cases at multiple geographical scales

Although the power of genetic surveillance tools has been acknowledged widely, there is an urgent need in malaria endemic countries for feasible and cost-effective tools to implement in national malaria control programs (NMCPs) that can generate evidence to guide malaria control and elimination strategies, especially in the case of Plasmodium vivax. Several genetic surveillance applications ('use cases') have been identified to align research, technology development, and public health efforts, requiring different types of molecular markers. Here we present a new highly-multiplexed deep sequencing assay (Pv AmpliSeq). The assay targets the 33-SNP vivaxGEN-geo panel for country-level classification, and a newly designed 42-SNP within-country barcode for analysis of parasite dynamics in Vietnam and 11 putative drug resistance genes in a highly multiplexed NGS protocol with easy workflow, applicable for many different genetic surveillance use cases. The Pv AmpliSeq assay was validated using: 1) isolates from travelers and migrants in Belgium, and 2) routine collections of the national malaria control program at sentinel sites in Vietnam. The assay targets 229 amplicons and achieved a high depth of coverage (mean 595.7 ± 481) and high accuracy (mean error-rate of 0.013 ± 0.007). P. vivax parasites could be characterized from dried blood spots with a minimum of 5 parasites/µL and 10% of minority-clones. The assay achieved good spatial specificity for between-country prediction of origin using the 33-SNP vivaxGEN-geo panel that targets rare alleles specific for certain countries and regions. A high resolution for within-country diversity in Vietnam was achieved using the designed 42-SNP within-country barcode that targets common alleles (median MAF 0.34, range 0.01-0.49. Many variants were detected in (putative) drug resistance genes, with different predominant haplotypes in the pvmdr1 and pvcrt genes in different provinces in Vietnam. The capacity of the assay for high resolution identity-by-descent (IBD) analysis was demonstrated and identified a high rate of shared ancestry within Gia Lai Province in the Central Highlands of Vietnam, as well as between the coastal province of Binh Thuan and Lam Dong. Our approach performed well in geographically differentiating isolates at multiple spatial scales, detecting variants in putative resistance genes, and can be easily adjusted to suit the needs in other settings in a country or region. We prioritize making this tool available to researchers and NMCPs in endemic countries to increase ownership and ensure data usage for decision-making and malaria policy.

A PCR-RFLP Technique to Assess the Geographic Origin of Plasmodium falciparum Strains in Central America

The elimination of malaria requires strengthening diagnosis and offering adequate and timely treatment. Imported cases of falciparum malaria represent a major challenge for pre-elimination areas, such as Central America, where chloroquine and primaquine continue to be used as first-line treatment. The pfs47 gene has been previously described as a precise molecular marker to track the geographic origin of the parasite. The aim of this study was to design a simple and low-cost technique using the polymorphic region of pfs47 to assess the geographic origin of P. falciparum strains. A PCR-RFLP technique was developed and evaluated using the MseI enzyme that proved capable of discriminating, with reasonable precision, the geographical origin of the parasites. This method could be used by national surveillance laboratories and malaria elimination programs in countries such as Honduras and Nicaragua in cases of malaria where an origin outside the Central American isthmus is suspected.

Genetic diversity of Plasmodium vivax reticulocyte binding protein 2b in global parasite populations

Background

Plasmodium vivax reticulocyte binding protein 2b (PvRBP2b) plays a critical role in parasite invasion of reticulocytes by binding the transferrin receptor 1. PvRBP2b is a vaccine candidate based on the negative correlation between antibody titers against PvRBP2b recombinant proteins and parasitemia and risk of vivax malaria. The aim of this study was to analyze the genetic diversity of the PvRBP2b gene in the global P. vivax populations.

Methods

Near full-length PvRBP2b nucleotide sequences (190–8349 bp) were obtained from 88 P. vivax isolates collected from the China–Myanmar border (n = 44) and Thailand (n = 44). An additional 224 PvRBP2b sequences were retrieved from genome sequences from parasite populations worldwide. The genetic diversity, neutral selection, haplotype distribution and genetic differentiation of PvRBP2b were examined.

Results

The genetic diversity of PvRBP2b was distributed unevenly, with peak diversity found in the reticulocyte binding region in the N-terminus. Neutrality analysis suggested that this region is subjected to balancing selection or population bottlenecks. Several amino acid variants were found in all or nearly all P. vivax endemic regions. However, the critical residues responsible for reticulocyte binding were highly conserved. There was substantial population differentiation according to the geographical separation. The distribution of haplotypes in the reticulocyte binding region varied among regions; even the two major haplotypes Hap_6 and Hap_8 were found in only five populations.

Conclusions

Our data show considerable genetic variations of PvRBPb in global parasite populations. The geographic divergence may pose a challenge to PvRBP2b-based vaccine development.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-022-05296-6.

Using deep learning to identify recent positive selection in malaria parasite sequence data

BACKGROUND

Malaria, caused by Plasmodium parasites, is a major global public health problem. To assist an understanding of malaria pathogenesis, including drug resistance, there is a need for the timely detection of underlying genetic mutations and their spread. With the increasing use of whole-genome sequencing (WGS) of Plasmodium DNA, the potential of deep learning models to detect loci under recent positive selection, historically signals of drug resistance, was evaluated.

METHODS

A deep learning-based approach (called "DeepSweep") was developed, which can be trained on haplotypic images from genetic regions with known sweeps, to identify loci under positive selection. DeepSweep software is available from https://github.com/WDee/Deepsweep .

RESULTS

Using simulated genomic data, DeepSweep could detect recent sweeps with high predictive accuracy (areas under ROC curve > 0.95). DeepSweep was applied to Plasmodium falciparum (n = 1125; genome size 23 Mbp) and Plasmodium vivax (n = 368; genome size 29 Mbp) WGS data, and the genes identified overlapped with two established extended haplotype homozygosity methods (within-population iHS, across-population Rsb) (~ 60-75% overlap of hits at P < 0.0001). DeepSweep hits included regions proximal to known drug resistance loci for both P. falciparum (e.g. pfcrt, pfdhps and pfmdr1) and P. vivax (e.g. pvmrp1).

CONCLUSION

The deep learning approach can detect positive selection signatures in malaria parasite WGS data. Further, as the approach is generalizable, it may be trained to detect other types of selection. With the ability to rapidly generate WGS data at low cost, machine learning approaches (e.g. DeepSweep) have the potential to assist parasite genome-based surveillance and inform malaria control decision-making.

Malaria in the 'Omics Era'

Genomics has revolutionised the study of the biology of parasitic diseases. The first Eukaryotic parasite to have its genome sequenced was the malaria parasite Plasmodium falciparum. Since then, Plasmodium genomics has continued to lead the way in the study of the genome biology of parasites, both in breadth-the number of Plasmodium species' genomes sequenced-and in depth-massive-scale genome re-sequencing of several key species. Here, we review some of the insights into the biology, evolution and population genetics of Plasmodium gained from genome sequencing, and look at potential new avenues in the future genome-scale study of its biology.

Distinctive genetic structure and selection patterns in Plasmodium vivax from South Asia and East Africa

Despite the high burden of Plasmodium vivax malaria in South Asian countries, the genetic diversity of circulating parasite populations is not well described. Determinants of antimalarial drug susceptibility for P. vivax in the region have not been characterised. Our genomic analysis of global P. vivax (n = 558) establishes South Asian isolates (n = 92) as a distinct subpopulation, which shares ancestry with some East African and South East Asian parasites. Signals of positive selection are linked to drug resistance-associated loci including pvkelch10, pvmrp1, pvdhfr and pvdhps, and two loci linked to P. vivax invasion of reticulocytes, pvrbp1a and pvrbp1b. Significant identity-by-descent was found in extended chromosome regions common to P. vivax from India and Ethiopia, including the pvdbp gene associated with Duffy blood group binding. Our investigation provides new understanding of global P. vivax population structure and genomic diversity, and genetic evidence of recent directional selection in this important human pathogen.

Reconstruction of Plasmodium vivax outbreaks in a low malaria endemic setting utilizing conventional restriction fragment length polymorphism

Suriname is on track to eliminate local malaria transmission. P. vivax malaria reemerged in March and September 2019 in the Amerindian village Palumeu, free of malaria for two years and concurrently, a case was reported in another village Alalaparoe. The outbreaks were contained through targeted interventions including Mass Drug Administration (MDA). Molecular outbreak analysis was performed on 23 dried blood spots (DBS) using combined polymerase chain reaction/restriction fragment length polymorphism (PCR-RFLP) with Pvmsp-1 F2 and Pvmsp-3α as polymorphic marker genes. Independent controls substantiated the discriminating capacities of the utilized PCR-RFLP method. All isolates from the first and second Palumeu outbreak shared a distinctive haplotype presuming single clonal lineage. An imported case probably triggered the first outbreak, while a delayed episode, prompted by withdrawal of drug pressure at the end of the prophylactic MDA, was suggested as source of the second outbreak. A diverging variant was demonstrated in Alalaparoe, implicating an infection from a different source. PCR-RFLP proved to be a useful molecular tool for P. vivax outbreak management in low endemic malaria settings.

Whole genome sequencing of Plasmodium vivax isolates reveals frequent sequence and structural polymorphisms in erythrocyte binding genes

Plasmodium vivax malaria is much less common in Africa than the rest of the world because the parasite relies primarily on the Duffy antigen/chemokine receptor (DARC) to invade human erythrocytes, and the majority of Africans are Duffy negative. Recently, there has been a dramatic increase in the reporting of P. vivax cases in Africa, with a high number of them being in Duffy negative individuals, potentially indicating P. vivax has evolved an alternative invasion mechanism that can overcome Duffy negativity. Here, we analyzed single nucleotide polymorphism (SNP) and copy number variation (CNV) in Whole Genome Sequence (WGS) data from 44 P. vivax samples isolated from symptomatic malaria patients in southwestern Ethiopia, where both Duffy positive and Duffy negative individuals are found. A total of 123,711 SNPs were detected, of which 22.7% were nonsynonymous and 77.3% were synonymous mutations. The largest number of SNPs were detected on chromosomes 9 (24,007 SNPs; 19.4% of total) and 10 (16,852 SNPs, 13.6% of total). There were particularly high levels of polymorphism in erythrocyte binding gene candidates including merozoite surface protein 1 (MSP1) and merozoite surface protein 3 (MSP3.5, MSP3.85 and MSP3.9). Two genes, MAEBL and MSP3.8 related to immunogenicity and erythrocyte binding function were detected with significant signals of positive selection. Variation in gene copy number was also concentrated in genes involved in host-parasite interactions, including the expansion of the Duffy binding protein gene (PvDBP) on chromosome 6 and MSP3.11 on chromosome 10. Based on the phylogeny constructed from the whole genome sequences, the expansion of these genes was an independent process among the P. vivax lineages in Ethiopia. We further inferred transmission patterns of P. vivax infections among study sites and showed various levels of gene flow at a small geographical scale. The genomic features of P. vivax provided baseline data for future comparison with those in Duffy-negative individuals and allowed us to develop a panel of informative Single Nucleotide Polymorphic markers diagnostic at a micro-geographical scale.

Population genomics reveals the expansion of highly inbred Plasmodium vivax lineages in the main malaria hotspot of Brazil

BACKGROUND

Plasmodium vivax is a neglected human malaria parasite that causes significant morbidity in the Americas, the Middle East, Asia, and the Western Pacific. Population genomic approaches remain little explored to map local and regional transmission pathways of P. vivax across the main endemic sites in the Americas, where great progress has been made towards malaria elimination over the past decades.

METHODOLOGY/PRINCIPAL FINDINGS

We analyze 38 patient-derived P. vivax genome sequences from Mâncio Lima (ML)-the Amazonian malaria hotspot next to the Brazil-Peru border-and 24 sequences from two other sites in Acre State, Brazil, a country that contributes 23% of malaria cases in the Americas. We show that the P. vivax population of ML is genetically diverse (π = 4.7 × 10-4), with a high polymorphism particularly in genes encoding proteins putatively involved in red blood cell invasion. Paradoxically, however, parasites display strong genome-wide linkage disequilibrium, being fragmented into discrete lineages that are remarkably stable across time and space, with only occasional recombination between them. Using identity-by-descent approaches, we identified a large cluster of closely related sequences that comprises 16 of 38 genomes sampled in ML over 26 months. Importantly, we found significant ancestry sharing between parasites at a large geographic distance, consistent with substantial gene flow between regional P. vivax populations.

CONCLUSIONS/SIGNIFICANCE

We have characterized the sustained expansion of highly inbred P. vivax lineages in a malaria hotspot that can seed regional transmission. Potential source populations in hotspots represent a priority target for malaria elimination in the Amazon.

Population genomics identifies a distinct Plasmodium vivax population on the China-Myanmar border of Southeast Asia

Plasmodium vivax has become the predominant malaria parasite and a major challenge for malaria elimination in the Greater Mekong Subregion (GMS). Yet, our knowledge about the evolution of P. vivax populations in the GMS is fragmental. We performed whole genome sequencing on 23 P. vivax samples from the China-Myanmar border (CMB) and used 21 high-coverage samples to compare to over 200 samples from the rest of the GMS. Using genome-wide single nucleotide polymorphisms (SNPs), we analyzed population differentiation, genetic structure, migration and potential selection using an array of methods. The CMB parasites displayed a higher proportion of monoclonal infections, and 52% shared over 90% of their genomes in identity-by-descent segments with at least one other sample from the CMB, suggesting preferential expansion of certain parasite strains in this region, likely resulting from the P. vivax outbreaks occurring during this study period. Principal component, admixture, fixation index and phylogenetic analyses all identified that parasites from the CMB were genetically distinct from parasites from eastern parts of the GMS (Cambodia, Laos, Vietnam, and Thailand), whereas the eastern GMS parasite populations were largely undifferentiated. Such a genetic differentiation pattern of the P. vivax populations from the GMS parasite was largely explainable through geographic distance. Using the genome-wide SNPs, we narrowed down to a set of 36 SNPs for differentiating parasites from different areas of the GMS. Genome-wide scans to determine selection in the genome with two statistical methods identified genes potentially under drug selection, including genes associated with antifolate resistance and genes linked to chloroquine resistance in Plasmodium falciparum.